VRG

Saint Louis University

Profile URL

https://talent.gravityer.com/vigneshwar-reddy-gangireddy

VIGNESHWAR REDDY GANGIREDDY

Backend Engineer with 1+ years in Java, Node.js & Distributed Systems

Saint Louis University

Hyderābād, Telangana, India

Since April 23, 2026

About

Backend Software Engineer specializing in designing scalable REST APIs, microservices, and distributed backend systems using Java, Node.js, PostgreSQL, Redis, Docker, CI/CD, and AWS. Experienced in concurrency handling, performance optimization, caching layers, high-availability system design, and distributed architectural patterns. Additional experience deploying ML inference pipelines and integrating AI/ML models into backend services.

Top Skills

JavaNode.JsPythonMicroservices

Skills

JavaNode.JsPythonRest ApisMicroservicesDockerGithub ActionsJenkinsLinuxPostgresqlMysqlScalabilityTensorFlowPyTorchScikit LearnModel OptimizationSQLExpress.JsSpring Boot

Education

Saint Louis University

Master Of Science · Computer Science

August 1, 2023 – June 30, 2025

KL University

Bachelor of Technology · Computer Science and Engineering (AI Specialization)

August 1, 2019 – June 30, 2023

Experience

OpenText

Developer Intern

August 1, 2022 – November 1, 2022

Bengaluru, Karnataka, India

AICTE

Cloud Intern

October 1, 2021 – December 1, 2021

India

Samsung PRISM

Audio Processing Intern

July 1, 2021 – March 1, 2022

Bengaluru, Karnataka, India

Projects

Job Recruitment Backend System

November 1, 2024 – Present

Built REST APIs for job posting, candidate search, and applicant tracking. Optimized SQL queries and added Redis caching, reducing search latency by 75%. Implemented distributed design patterns for high availability.

View Project

Smart Assistance for Visually Impaired

March 1, 2023 – Present

Deployed a computer vision inference pipeline using FastAPI. Optimized model execution and batching to reduce inference latency by 35%. Integrated CV + NLP components for real-time user feedback.

Travel Tourism and Hospitality Management Web App

November 1, 2021 – Present

Developed backend APIs for booking, itinerary generation, and user management. Implemented authentication, CRUD operations, and server-side validation. Optimized MongoDB queries for large-scale travel datasets.

URL Shortener Backend

March 1, 2020 – Present

Implemented Base62 encoding with Redis write-through caching for fast lookups. Optimized SQL queries and indexing to reduce latency. Added rate limiting, analytics logging, and fault-tolerant routing.

Certifications

Fundamentals of Data Analytics

NASSCOM

January 1, 2023 – Present

Azure AZ-900

Microsoft Certified

January 1, 2023 – Present

Cloud Infrastructure Foundations Associate

Oracle

January 1, 2022 – Present

Advanced RPA Professional

Automation Anywhere

January 1, 2022 – Present

Key Strengths

Strong practical experience in backend development using Node.js, Java, and Python, evidenced by diverse personal projects.
Proficiency in designing and optimizing REST APIs, including microservices architecture and distributed design patterns.
Demonstrated ability in database optimization (SQL, MongoDB) and caching (Redis) to improve system performance.
Experience with performance tuning, reducing latency in backend systems and computer vision pipelines.
Exposure to cloud platforms (AWS, Azure, Oracle) and containerization (Docker), indicating foundational DevOps understanding.

Skill Analysis

MERN Stack Development

★★★★★

77%

The candidate scored 77% on the MERN : Intern test, indicating a good grasp of fundamental and intermediate concepts across the MERN stack.

MongoDBReactNode.jsJavaScriptNoSQLCSSSass

Strengths

Demonstrated solid understanding of MERN stack components, particularly Node.js and MongoDB.
Achieved a strong score in core JavaScript and NoSQL concepts, indicating practical backend development capabilities.

Limitations

While strong, the 77% score suggests potential areas for improvement in specific MERN components or advanced front-end (React, CSS/Sass) concepts for senior-level proficiency.

Cultural & Operational Fit

Cultural Fit Analysis

The psychometric test score of 48% raises significant concerns regarding cultural fit. This low score points to potential challenges in areas such as logical reasoning, work attitude, stress management, and team collaboration, which are essential for thriving in a collaborative and demanding senior engineering environment.

Soft Skills & Operational Fit

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Key Strengths

Strong practical experience in backend development using Node.js, Java, and Python, evidenced by diverse personal projects.
Proficiency in designing and optimizing REST APIs, including microservices architecture and distributed design patterns.
Demonstrated ability in database optimization (SQL, MongoDB) and caching (Redis) to improve system performance.
Experience with performance tuning, reducing latency in backend systems and computer vision pipelines.
Exposure to cloud platforms (AWS, Azure, Oracle) and containerization (Docker), indicating foundational DevOps understanding.

Skill Analysis

MERN Stack Development

★★★★★

77%

The candidate scored 77% on the MERN : Intern test, indicating a good grasp of fundamental and intermediate concepts across the MERN stack.

MongoDBReactNode.jsJavaScriptNoSQLCSSSass

Strengths

Demonstrated solid understanding of MERN stack components, particularly Node.js and MongoDB.
Achieved a strong score in core JavaScript and NoSQL concepts, indicating practical backend development capabilities.

Limitations

While strong, the 77% score suggests potential areas for improvement in specific MERN components or advanced front-end (React, CSS/Sass) concepts for senior-level proficiency.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit